code: def convert_to_comparison_proto(
      dfs: Iterable[Tuple[str, pd.DataFrame]]
  ) -> facet_feature_statistics_pb2.DatasetFeatureStatisticsList:
      """
      Converts a collection of named stats DataFrames to a single DatasetFeatureStatisticsList proto.
      :param dfs: The named "glimpses" that contain the DataFrame. Each "glimpse"
          DataFrame has the same properties as the input to `convert_to_proto()`.
      :return: A DatasetFeatureStatisticsList proto which contains a translation
          of the glimpses with the given names.
      """
      feature_stats_list = (
          facet_feature_statistics_pb2.DatasetFeatureStatisticsList()
      )
      for name, df in dfs:
          if not df.empty:
              proto = convert_to_dataset_feature_statistics(df)
              proto.name = name
              feature_stats_list.datasets.append(proto)
      return feature_stats_list
  
file_path: mlflow/mlflow/recipes/cards/pandas_renderer.py
imports: import base64
  import sys
  from typing import Iterable, Tuple, Union
  import numpy
  import pandas
  from packaging.version import Version
  from mlflow.exceptions import MlflowException
  from mlflow.protos import facet_feature_statistics_pb2
  from mlflow.recipes.cards import histogram_generator
label_desc: Use image node_id 6 for calling a global function with example usage: convert_to_comparison_proto(dfs) and returns: feature_stats_list